Pool water disinfection is vital to prevent microbial pathogens. However, potentially hazardous disinfection by-products (DBP) are formed from the reaction between disinfectants and organic/inorganic precursors. The aim of this study was to evaluate the presence of DBPs in various swimming pool types in Brisbane, Australia, including outdoor, indoor and baby pools, and the dynamics after a complete water renewal. Chemical analysis of 36 regulated and commonly found DBPs and total adsorbable organic halogens as well as in vitro bioassays targeting cytotoxicity, oxidative stress and genotoxicity were used to evaluate swimming pool water quality. Dichloroacetic acid and trichloroacetic acid dominated in the pool water samples with higher levels (up to 2600 μg/L) than the health guideline values set by the Australian Drinking Water Guidelines (100 μg/L). Chlorinated DBPs occurred at higher concentrations compared to tap water, while brominated DBPs decreased gradually with increasing pool water age. Biological effects were expressed as chloroacetic acid equivalent concentrations and compared to predicted effects from chemical analysis and biological characterisation of haloacetic acids. The quantified haloacetic acids explained 35-118% of the absorbable organic halogens but less than 4% of the observed non-specific toxicity (cytotoxicity), and less than 1% of the observed oxidative stress response and genotoxicity. While the DBP concentrations in Australian pools found in this study are not likely to cause any adverse health effect, they are higher than in other countries and could be reduced by better hygiene of pool users, such as thorough showering prior to entering the pool and avoiding urination during swimming.

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Obesity is associated with 14 types of cancers, with specific lipids contributing to each hallmark of cancer.

The rapid evolution of mass spectrometry (MS)-based lipidomics has enabled the simultaneous measurement of numerous lipid classes. With lipidomics datasets becoming increasingly available, lipidomic-focused software tools are required to facilitate data analysis as well as mining of public datasets, integrating lipidomics-unique molecular information, such as lipid class, chain length and unsaturation. To address this need, we developed lipidr, an open-source R/Bioconductor package for data mining and analysis of lipidomics datasets. lipidr implements a comprehensive lipidomic-focused analysis workflow for targeted and untargeted lipidomics. lipidr imports numerical matrices, Skyline exports and Metabolomics Workbench files directly into R, automatically inferring lipid class and chain information from lipid names. Through integration with the Metabolomics Workbench API, users can search, download and reanalyze public lipidomics datasets seamlessly. lipidr allows thorough data inspection, normalization, uni-and multivariate analyses, displaying results as interactive visualizations.To enable interpretation of lipid class, chain length and total unsaturation data, we also developed and implemented a novel Lipid Set Enrichment Analysis. A companion online guide with two live example datasets is presented at https://www.lipidr.org/.We expect that the ease of use and innovative features of lipidr allow the lipidomics research community to gain novel detailed insights from lipidomics data.